R is a truly terrible language with a handful of bright spots, such as it's visualization libraries.
The boost you get from the slightly better expressiveness of R over something like Julia or Python is not worth the headaches you'll run into down the road in trying to maintain whatever you wrote 6 months later, or God forbid, trying to integrate your code into someone else's work.
R was my first language and in hindsight that was a HUGE mistake. So much of the R code out there is horribly written, and even when it isn't you still have to deal with all of the issues the author here points out. If you pick up R as your first language, you will end up picking up all sorts of bad habits;
R is fine if you're working solo and you don't plan on maintaining or reusing or reusing your code. For everything else, R is garbage. It took me a year or more to undo all of the bad habits I picked up learning R.
I don't agree with the "worse is better" comparison in the comments here. "Worse is Better" was meant to refer to the idea of "Don't make the perfect the enemy of the good", among other things. It was not meant to be used as a justification for poor design. If anything, python for data analysis fits the "worse is better" philosophy much better than R. It's not as well optimized for data work compared to R, but it's much simpler, more consistent, less error prone, and it plays well with others.